{"id":"W4241023809","doi":"10.1021/acs.analchem.7b00807","title":"Immunohistochemistry Microarrays","year":2017,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University and Génome Québec Innovation Centre; McGill University Health Centre","funders":"Canadian Cancer Society Research Institute; Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Canada Foundation for Innovation","keywords":"Tissue microarray; Immunohistochemistry; Staining; Multiplex; Stain; Pathology; Chemistry; Antibody; Protein microarray; Antibody microarray; Microarray; Molecular biology; Biology; Bioinformatics; Medicine; Gene expression; Biochemistry; Immunology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008625863,0.0001434218,0.0001165421,0.000007702474,0.000298424,0.00009586893,0.000577557,0.0001966339,0.0002893374],"category_scores_gemma":[0.0002071245,0.0001422861,0.0001243109,0.00002287232,0.0002140392,0.000004129738,0.0001773451,0.0001224018,0.00003744541],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002115151,"about_ca_system_score_gemma":0.00007841253,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005768455,"about_ca_topic_score_gemma":2.992921e-7,"domain_scores_codex":[0.9990849,0.000006919759,0.0001654154,0.0003944302,0.0001321371,0.0002162061],"domain_scores_gemma":[0.9983802,0.000002945366,0.0001226092,0.001283125,0.00007332617,0.0001377535],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003022934,0.00003254094,0.001216571,0.00001868483,0.00002533931,0.000002277978,0.00000317918,0.000001156948,0.9735944,0.00003152574,0.02428762,0.0007564564],"study_design_scores_gemma":[0.0003182617,0.00001123464,0.001869451,0.00001185158,0.00001666071,0.00001252237,0.00002730805,0.000066775,0.8788532,0.00006612904,0.1185597,0.0001868824],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7999764,0.0004406078,0.0007791566,0.0008935322,0.0001462928,0.00006343273,0.00001150094,0.00002537316,0.1976637],"genre_scores_gemma":[0.9642301,0.00006254276,0.0001444722,0.0001450583,0.0003898875,0.00001522437,0.0000760796,0.00001738501,0.03491927],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1642537,"threshold_uncertainty_score":0.5802259,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01528924491419036,"score_gpt":0.3062093726951723,"score_spread":0.2909201277809819,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}